Search Filters

Search Results

Found 2 results

510(k) Data Aggregation

    K Number
    K192259
    Date Cleared
    2019-09-20

    (30 days)

    Product Code
    Regulation Number
    864.3700
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    Philips Electronics Nederland B.V.

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Philips IntelliSite Pathology Solution (PIPS) is an automated digital slide creation, viewing, and management system. The PIPS is intended for in vitro diagnostic use as an aid to the pathologist to review and interpret digital images of surgical pathology slides prepared from formalin-fixed paraffin embedded (FFPE) tissue. The PIPS is not intended for use with frozen section, cytology, or non-FFPE hematopathology specimens.

    The PIPS comprises the Image Management System (IMS), the Ultra Fast Scanner (UFS) and display. The PIPS is for creation and viewing of digital images of scanned glass slides that would otherwise be appropriate for manual visualization by conventional light microscopy. It is the responsibility of a qualified pathologist to employ appropriate procedures and safeguards to assure the validity of the interpretation of images obtained using PIPS.

    Device Description

    Philips IntelliSite Pathology Solution (PIPS) is an automated digital slide creation, viewing, and management system. PIPS consists of two sub-systems and a display component:

    • . Image Management System (IMS)
    • Ultra Fast Scanner (UFS)
    • . Display
    AI/ML Overview

    The provided document is a 510(k) Summary for a minor modification to an existing device, the Philips IntelliSite Pathology Solution (PIPS). The modification is a new display panel. Therefore, the information primarily focuses on demonstrating that this new panel does not adversely affect the device's performance compared to the predicate device.

    Here's the breakdown of the requested information based on the provided text:

    1. A table of acceptance criteria and the reported device performance

    The document does not explicitly state "acceptance criteria" in the format of a table with specific numerical thresholds for performance. Instead, it refers to compliance with international and FDA-recognized consensus standards and verification tests. The "reported device performance" is framed as demonstrating similarity to the predicate device and compliance with these standards.

    Acceptance Criteria CategoryReported Device Performance (with new display panel)
    Compliance with StandardsComplies with IEC 60601-1-2 (4th Ed), ANSI/AAMI ES60601-1:2005/(R)2012, ISO 14971:2007, IEC 62471: 2006; EN 62471: 2008.
    Technological CharacteristicsSimilar technological characteristics (Panel type, Technology, Physical display size) to the predicate device (Bi-Search Korea Inc./LG display Co., Ltd. panel). The new panel is from Innolux Corporation.
    Display Performance Tests (following TPA guidance)Spatial resolution: Verified to not be affected.
    Pixel defects: Verified to not be affected.
    Temporal response: Verified to not be affected.
    Grayscale: Verified to not be affected.
    Luminance uniformity and Mura test: Verified to not be affected.
    Stability of luminance and chromaticity: Verified to not be affected.
    Specular and diffuse reflection coefficients: Verified to not be affected.
    Gray tracking: Verified to not be affected.
    Color scale response: Verified to not be affected.
    sRGB (standard Red Green Blue) color gamut: Verified to not be affected.
    Safety and EffectivenessDemonstrated to be as safe and effective as the predicate device without raising any new safety and/or effectiveness concerns.

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    The document primarily describes non-clinical performance testing of a new display panel. It does not mention a "test set" in the context of patient data or clinical imaging for diagnostic performance evaluation. The tests performed were on the display itself.

    • No information on sample size for a test set of patient data.
    • No information on data provenance (country of origin, retrospective/prospective).
    • The tests were performed on the hardware (display panel).

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    This information is not applicable. The study described is not a clinical study on diagnostic accuracy or interpretation where expert ground truth would be established. It is a non-clinical study verifying the technical performance of a hardware component (display).

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    This information is not applicable for the same reason as point 3.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

    No MRMC comparative effectiveness study was done. The device (Philips IntelliSite Pathology Solution) is a whole slide imaging system, not an AI-assisted diagnostic tool. This submission is for a hardware change (display panel) to an existing cleared device. The document explicitly states: "The proposed device with the new display panel did not require clinical performance data since substantial equivalence to the currently marketed predicate device was demonstrated with the following attributes: - Intended Use / Indications for Use, - Technological characteristics, - Non-clinical performance testing, and - Safety and effectiveness." Therefore, no improvement with AI assistance was measured or is relevant to this specific submission.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

    This is not applicable. The device is a whole slide imaging system, not an algorithm, and this submission concerns a display hardware change.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

    This is not applicable as there was no clinical study involving patient data or diagnostic interpretation for which ground truth would be established. The "ground truth" for the non-clinical tests would be the established technical specifications and performance limits for display devices.

    8. The sample size for the training set

    This is not applicable. The device is a whole slide imaging system, not an AI/ML algorithm that requires a "training set."

    9. How the ground truth for the training set was established

    This is not applicable for the same reason as point 8.

    Ask a Question

    Ask a specific question about this device

    K Number
    K171055
    Date Cleared
    2017-07-06

    (87 days)

    Product Code
    Regulation Number
    878.4810
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    Philips Electronics Nederland B.V.

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Philips BlueControl is intended to emit energy in the blue region of the spectrum, is generally indicated to treat dermatological conditions and specifically indicated to treat mild psoriasis vulgaris.

    Device Description

    The Philips BlueControl is a rechargeable battery-operated, wearable device for delivery of blue light to treat mild psoriasis vulgaris. It is a prescription device designed for home use. The Philips BlueControl is sold as a kit, which contains the following items: Components: o BlueControl Device o Fixation Strap (Device Holder and Slings) o Power Supply (USB Cable, Adapter and Charger) Accessory: ● 0 Carrying Case Instructions for Use.

    AI/ML Overview

    The Philips BlueControl device is intended to treat mild psoriasis vulgaris. The provided text outlines the performance data, including clinical studies, that support the substantial equivalence determination for this device.

    1. Table of Acceptance Criteria and Reported Device Performance:

    The document does not explicitly present a table of acceptance criteria for its clinical performance. Instead, it describes clinical studies and their outcomes as evidence of effectiveness. The primary endpoint for effectiveness was a statistically significant improvement in Local Psoriasis Area and Severity Index (LPASI) scores.

    Acceptance Criteria CategorySpecific Metric (Inferred)Acceptance Threshold (Inferred)Reported Device Performance
    Clinical EffectivenessChange from Baseline (CfB) of the LPASI at week 12Statistically significant improvement in treated plaques compared to control plaques.- The primary endpoint, change from baseline (CfB) of the LPASI at week 12, revealed a significant improvement of the treated compared to the control plaques (△CfB: -0.92 ± 1.10, p = 0.0005, t test; p = 0.0006, Wilcoxon signed-rank test; mean 95% CI –1.38, –0.45).
    • The mean change from baseline to week 12 was -2.38 (-3.02 to -1.73) in the treated plaque and -1.46 (-2.13 to -0.79) in the control plaque. |
      | Safety | Incidence of serious adverse events (SAEs) related to treatment | No serious adverse events considered related to any of the studied treatment regimen. | - No serious adverse events were considered related to any of the studied treatment regimen.
    • All 16 adverse events observed during the study were evaluated. No serious adverse events were reported. None of the adverse events were device-related or treatment-related.
    • Hyperpigmentation (tanning) was expected and reported, which reduced within a few days after treatment completion. No other device-related adverse effects were observed. |

    2. Sample Size Used for the Test Set and Data Provenance:

    • Sample Size for Test Set: N=23 enrolled subjects in the main clinical study, with each subject having treated and control plaques.
    • Data Provenance: Prospective, clinical studies conducted in Europe per ISO 14155 (Clinical investigation of medical devices for human subjects -- Good clinical practice).

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:

    The document does not explicitly state the number or qualifications of experts used to establish the ground truth for the test set (i.e., evaluate LPASI scores). It mentions that "psoriasis severity was evaluated using the Local Psoriasis Area and Severity Index (LPASI), a modified version of the validated PASI." This typically implies trained clinicians or dermatologists, but specific details are not provided.

    4. Adjudication Method for the Test Set:

    The document does not describe a specific adjudication method (e.g., 2+1, 3+1) for the LPASI evaluations in the test set.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

    No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was mentioned. The study design involved comparing treated plaques to control plaques within the same subjects, rather than comparing human readers with and without AI assistance.

    6. Standalone (Algorithm Only) Performance:

    Not applicable. The Philips BlueControl is a light therapy device, not an AI algorithm, so a standalone algorithm-only performance assessment is not relevant in this context.

    7. Type of Ground Truth Used:

    The ground truth for effectiveness was based on clinical assessment using the Local Psoriasis Area and Severity Index (LPASI), performed by presumably clinical investigators or dermatologists as part of the clinical studies. For safety, it was adverse event reporting and evaluation.

    8. Sample Size for the Training Set:

    Not applicable. The Philips BlueControl is a medical device, not an AI/machine learning algorithm, so there is no "training set" in the conventional sense for algorithm development. The device's performance is based on its physical properties and clinical evaluation in humans.

    9. How the Ground Truth for the Training Set Was Established:

    Not applicable, as there is no training set for an AI algorithm. The device's design and parameters are based on scientific understanding of blue light therapy for psoriasis and established medical device development standards, rather than AI model training.

    Ask a Question

    Ask a specific question about this device

    Page 1 of 1